• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.372-375
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• 2014

A monopulse based on maximum likelihood(ML) in jamming scenario can suppress jamming signal using an inverse matrix of a covariance matrix. In order to achieve adequate suppression of jamming signal, the sufficient number of snapshots is required. However, this is not possible in high PRF scenario, which hinders a real-time tracking. Moreover, even with the large number of snapshots, the estimation accuracy of the target direction is decreased in low JNR(Jammer to Noise Ratio) due to insufficient jammer suppression. In this paper, we propose a monopulse algorithm that doesn't degrade performance significantly with a small number of snapshots and in low JNR. We show its derivation that exploits noise-jammer subspace of a covariance matrix, along with its performance through simulation.

• Investigative Magnetic Resonance Imaging
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• v.20 no.4
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• pp.215-223
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• 2016

Purpose: The management of metal-induced field inhomogeneities is one of the major concerns of distortion-free magnetic resonance images near metallic implants. The recently proposed method called "Slice Encoding for Metal Artifact Correction (SEMAC)" is an effective spin echo pulse sequence of magnetic resonance imaging (MRI) near metallic implants. However, as SEMAC uses the noisy resolved data elements, SEMAC images can have a major problem for improving the signal-to-noise ratio (SNR) without compromising the correction of metal artifacts. To address that issue, this paper presents a novel reconstruction technique for providing an improvement of the SNR in SEMAC images without sacrificing the correction of metal artifacts. Materials and Methods: Low-rank approximation in each coil image is first performed to suppress the noise in the slice direction, because the signal is highly correlated between SEMAC-encoded slices. Secondly, SEMAC images are reconstructed by the best linear unbiased estimator (BLUE), also known as Gauss-Markov or weighted least squares. Noise levels and correlation in the receiver channels are considered for the sake of SNR optimization. To this end, since distorted excitation profiles are sparse, $l_1$ minimization performs well in recovering the sparse distorted excitation profiles and the sparse modeling of our approach offers excellent correction of metal-induced distortions. Results: Three images reconstructed using SEMAC, SEMAC with the conventional two-step noise reduction, and the proposed image denoising for metal MRI exploiting sparsity and low rank approximation algorithm were compared. The proposed algorithm outperformed two methods and produced 119% SNR better than SEMAC and 89% SNR better than SEMAC with the conventional two-step noise reduction. Conclusion: We successfully demonstrated that the proposed, novel algorithm for SEMAC, if compared with conventional de-noising methods, substantially improves SNR and reduces artifacts.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.169-177
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• 2006

In this paper, we present an efficient image reconstruction method which is suited to remove various noise generated from measurement using X-ray attenuation. To be specific, we present a wavelet method to efficiently remove ring artifacts, which are caused by inevitable mechanical error in X-ray emitters and detectors. and streak artifacts, which are caused by general observation errors and Fourier transform-based reconstruction process. To remove ring artifacts related noise from projections, we suggest to estimate the noise intensity by using the fact that the noise related to ring artifacts has a strong correlation in the angle direction, and remove them by using wavelet shrinkage. We also suggest to use wavelet-vaguelette decomposition for general-purpose noise removal and image reconstruction. Through simulation studies. we show that the proposed method provides a better result in ring artifact removal and image reconstruction over the traditional Fourier transform-based methods.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.61-68
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• 2018

This paper describes design of a 10.525 GHz self oscillating mixer semiconductor IC chip combining voltage controlled oscillator and frequency mixer using silicon CMOS technology for Doppler radar applications. The p-core type VCO included in the self oscillating mixer minimizes the noise contained in the transmitted signal. This noise minimization increases the sensing distance and acts in a direction favorable to the reaching distance and the sensitivity of the motion detection sensor. Simulation results for phase noise show that a VCO designed as a P-core has a noise characteristic of -106.008 dBc / Hz at 1 MHz offset and -140.735 dBc / Hz at 25 MHz offset compared to a VCO designed with N-core and NP-core showed excellent noise characteristics. If a self-oscillating mixer is implemented using a p-core designed VCO in this study, a motion sensor with excellent range and reach sensitivity will be produced.

• Journal of Mechanical Science and Technology
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• v.16 no.11
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• pp.1395-1403
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• 2002

The characteristics of gear meshing vibration undesgo change as the vibration is transmitted from the gear to the housing. Therefore, vibration transmission characteristics of helical gear systems must be understood before the effective methods of reducing gear noise can be found. In this work, using a helical gear with different lead errors, the gear vibration in the rotational direction and the bearing vibration are measured. The frequency characteristics of gear and bearing vibration are investigated and a comparson is also provided.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.525-533
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• 2003

In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.495-498
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• 1999

In this paper, we propose the adaptive Odd/Even Multi-shell Median Filter(adaptive O/E MMF) to improve the defect that Modified Multi-shell Median Filter(MMMF) can not recover missing lines of vertical and cross direction. This filter uses odd/even multi-shells and new proposed threshold strategy The performance of the proposed filter is evaluated over image 'airfield 'by using MATLAB. As the proposed threshold strategy eliminate the number of redundant replacement, it suppresses impulse noise and recovers missing lines.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1799-1802
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• 2003

This paper has been studied a Adaptive feature-factors based fingerprints recognition in many biometrics. we study preprocessing and matching method of fingerprints image in various circumstances by using optical fingerprint input device. The Fingerprint Recognition Technology had many development until now. But, There is yet many point which the accuracy improves with operation speed in the side. First of all we study fingerprint classification to reduce existing preprocessing step and then extract a Feature-factors with direction information in fingerprint image. Also in the paper, we consider minimization of noise for effective fingerprint recognition system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.16-22
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• 1993

As a method of separating the signal arriving from a desired direction in the presence of noise and interfering signals, a linearly constrained adaptive beamformer based on the escalator (Gram-Schmidt) structure is presented. The weights are chosen to minimize local output power subject to the response constraint. The performances of the proposed escalator adaptive beamformer are compared with those of cascade adaptive beamformer via computer simulations.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.587-592
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• 2004

Pixel classification is one of basic issues of image processing. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time, a pixel classification scheme based on image information scales is proposed. The proposed method is overcome that computation amount become greater and contents easily get turned. And image directional scales has excellent anti-noise performance. In the result of experiment. good efficiency is showed compare with other methods.